The primary goal of this SBIR project is to create an integrated software system ("SocioMetrica") facilitating the application of social network methods for use in HIV and drug abuse epidemiology, prevention, and control. Because of the importance of social network mechanisms in human behavior, the software is also being designed to have wider commercial use in research, public health, government, and corporate markets. The public health value is substantial, because while it is relatively easy and inexpensive to gather egocentric nomination data (there are many existing data sets of this type), it is slower, more difficult, and costly to obtain sociometric data. Phase 1 focused on the problem of linking members of large or unbounded networks, such as drug abusers in communities. The LinkAlyzer program matches and links egocentric records to construct sociometric data, allowing more complete network models to be applied. The approach was tested with a HIV drug abuse data set with 15,000 records and 100 million potential matches, generating a network model with results that support validity. Phase II will create and test a larger SocioMetrica package of applications (including LinkAlyzer) designed to solve problems of commercial value. Assessment functions will be added to assist in gathering egocentric data. An extended set of social network measures will be implemented, and a platform will be created making it easier for users to implement their own network algorithms. Internet architecture will provide users with optional access to low-cost processing from powerful servers. This architecture will simplify software distribution, maintenance, and user support, and will facilitate multi-site project operations and data management. Iterative testing and validation will be done with consultants and potential customers using new and existing data. [unreadable] [unreadable]